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Microsoft AI-900 Certification Exam covers a wide range of topics related to AI and machine learning, including fundamental concepts such as machine learning models, data analysis, and natural language processing. AI-900 exam also covers more advanced topics such as computer vision, speech recognition, and intelligent decision-making. Microsoft Azure AI Fundamentals certification exam is designed to test an individual's knowledge of AI concepts and their ability to apply them to real-world scenarios using Microsoft Azure services.
NEW QUESTION # 174
For each of the following statements, select Yes if the statement is true. Otherwise, select No.
NOTE: Each correct selection is worth one point.
Answer:
Explanation:
Reference:
https://azure.microsoft.com/en-us/services/machine-learning/automatedml/#features
NEW QUESTION # 175
For each of the following statements, select Yes If the statement is true. Otherwise, select No.
NOTE: Each correct selection is worth one point.
Answer:
Explanation:
Explanation:
Location of a damaged product # Yes
Multiple instances of the same product # Yes
Multiple types of damaged products # Yes
All three statements are Yes, because they correctly describe the capabilities of object detection, one of the major workloads in computer vision, as defined in the Microsoft Azure AI Fundamentals (AI-900) study guide and Microsoft Learn module: "Describe features of computer vision workloads on Azure." Object detection is an advanced computer vision technique that allows AI systems not only to classify objects within an image but also to locate them by drawing bounding boxes around each detected object. This differentiates it from simple image classification, which only identifies what objects exist in an image without specifying their locations.
* Identifying the location of a damaged product - YesAccording to Microsoft Learn, object detection can return the coordinates or bounding boxes for recognized objects. Therefore, if the model is trained to detect damaged products, it can pinpoint exactly where those defects appear within an image.
* Identifying multiple instances of a damaged product - YesObject detection models can detect multiple objects of the same class in one image. For instance, if an image contains several damaged products, each will be identified and marked individually. This feature supports tasks such as automated quality inspection in manufacturing, where several defective units may appear simultaneously.
* Identifying multiple types of damaged products - YesObject detection can also distinguish different classes of objects. When trained on multiple labels (e.g., cracked, scratched, or broken items), the model can detect and classify each type of damage in one image.
In Microsoft's AI-900 framework, object detection is presented as a critical part of computer vision workloads capable of locating and classifying multiple objects and categories within visual content.
NEW QUESTION # 176
For each of the following statements, select Yes if the statement is true. Otherwise, select No.
NOTE: Each correct selection is worth one point.
Answer:
Explanation:
Explanation
Box 1: Yes
Azure Machine Learning designer lets you visually connect datasets and modules on an interactive canvas to create machine learning models.
Box 2: Yes
With the designer you can connect the modules to create a pipeline draft.
As you edit a pipeline in the designer, your progress is saved as a pipeline draft.
Box 3: No
Reference:
https://docs.microsoft.com/en-us/azure/machine-learning/concept-designer
NEW QUESTION # 177
A medical research project uses a large anonymized dataset of brain scan images that are categorized into predefined brain haemorrhage types.
You need to use machine learning to support early detection of the different brain haemorrhage types in the images before the images are reviewed by a person.
This is an example of which type of machine learning?
Answer: C
NEW QUESTION # 178
For each of the following statements, select Yes if the statement is true. Otherwise, select No.
NOTE: Each correct selection is worth one point.
Answer:
Explanation:
Explanation:
These answers align with the Microsoft Azure AI Fundamentals (AI-900) Official Study Guide and the Microsoft Learn module "Explore conversational AI in Microsoft Azure."
1. A webchat bot can interact with users visiting a website # Yes
This statement is true. The Azure Bot Service allows developers to create intelligent chatbots that can be integrated into a webchat interface. This enables visitors to interact with the bot directly from a website, asking questions and receiving automated responses. This is a typical use case of conversational AI, where natural language processing (NLP) is used to interpret and respond to user input conversationally.
2. Automatically generating captions for pre-recorded videos is an example of conversational AI # No This statement is false. Automatically generating captions from video content is an example of speech-to-text (speech recognition) technology, not conversational AI. While it uses AI to convert spoken words into text, it lacks the two-way interactive communication characteristic of conversational AI. This task is typically handled by the Azure AI Speech service, which transcribes spoken content.
3. A smart device in the home that responds to questions such as "What will the weather be like today?" is an example of conversational AI # Yes This statement is true. Smart home assistants that engage in dialogue with users are powered by conversational AI. These devices use speech recognition to understand spoken input, natural language understanding (NLU) to determine intent, and speech synthesis (text-to-speech) to respond audibly. This represents the full conversational AI loop, where machines communicate naturally with humans.
NEW QUESTION # 179
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